Are Virtual Forests Just for Relaxation, or Can They Enhance the Benefits of Therapy?
Bibliographic record
Abstract
Forest bathing (Shinrin-Yoku in Japanese) is used as an intervention for improving mental health, with VR being used to create virtual forests for relaxation. BACKGROUND/OBJECTIVES: In this research, we added therapeutic intent to a virtual forest with the goal of reducing social anxiety, with and without therapeutic instruction. METHODS: Fifty-eight first-year psychology students were randomly assigned to one of three conditions: virtual forest only, therapeutic exercises only, and both combined. RESULTS: All three conditions enhanced restorative effects equally. However, only the therapeutic exercise-only condition showed a tendency to reduce social anxiety. Participants in the combined condition reported more positive experiences and showed better comprehension of therapy content in the virtual forest. CONCLUSIONS: While the non-VR approach may offer immediate relaxation and possible anxiety reduction, combining the virtual forest with therapeutic exercises may yield better outcomes for sustained engagement and understanding over multiple therapeutic sessions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".